DHNs simulation data

This simulation dataset provides the topology structures of four different District Heating Networks (DHNs), along with randomly selected consumer clusters. It features high-resolution, with 1-minute time step, simulation results for 5.5 months, including water temperatures, mass flow rates, consumer substation heating demands, and heat source power productions. This data serves as the foundation for training, validating and testing diverse neural networks models to learn clusters underlying physics. Publicly available training and data pipeline code on Github [https://github.com/drod-96/smart_clusters_v1] facilitates data extraction for our machine learning models and post-treatment.